Machine learning the Higgs-top CP measurement at the LHC

開催日時

2024/6/11(火)11:00〜12:00

開催場所

研究本館セミナールームとzoom

講演者

Rahool Kumar (IPMU)

言語

英語

お問い合わせ

Ahmed Hammad/Hamed-AT-post.kek.jp

概要

The conventional approach to LHC analysis involves comparing the measured data to Monte Carlo simulations. These simulations start at the hard-scattering level, where the potential for new physics is maximal, and proceed through various stages, including showering, hadronization, and detector response. Unfortunately, each stage introduces complexities, resulting in a convoluted representation of the true underlying physics at the simulated detector level. Events measured at the LHC detector are also somewhat convoluted versions of the true underlying physics due to various latent effects. Eliminating these convolutions is essential for a direct comparison between theoretical predictions and measured data, which can be achieved through the process of ‘Unfolding’, where measured events are directly mapped to the hard-scattering level.